Case Study: petaFuel thwarts credit card fraud and improves application performance with Elastic Observability

petaFuel optimizes application and operational performance, and blocks credit card fraud with Elastic Observability

petaFuel, a certified payment provider and credit card processor, needed better visibility into application performance, incident management, and fraud risk across its mobile and multi-channel payment services. To meet those demands, the company turned to Elastic Observability to improve software quality and monitor customer and merchant behavior while keeping pace with growth and security requirements.

With Elastic, petaFuel centralized log analysis, error detection, and real-time event notifications, using Kibana and machine learning to speed root-cause analysis, fine-tune applications, and identify suspicious transactions. Elastic helped petaFuel reduce application errors by up to 15% for data-focused applications and cut credit card fraud by 2 basis points, while improving SLA performance and enabling faster response to threats.

petaFuel

Ludwig Adam

Chief Technology Officer